Random texts exhibit Zipf´s-law-like word frequency distribution

It is shown that the distribution of word frequencies for randomly generated texts is very similar to Zipf´s law observed in natural languages such as English. The facts that the frequency of occurrence of a word is almost an inverse power law function of its rank and the exponent of this inverse power law is very close to 1 are largely due to the transformation from the word´s length to its rank, which stretches an exponential function to a power law function